Instructions to use emvecchi/umod_constructiveness with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use emvecchi/umod_constructiveness with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("roberta-base") model.load_adapter("emvecchi/umod_constructiveness", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model_head.bin from emvecchi/umod_constructiveness: direct link, hf CLI and curl.
- Browser
- Download file 2.37 MB
-
https://huggingface.co/emvecchi/umod_constructiveness/resolve/main/pytorch_model_head.bin
- Command line
-
hf download hf://emvecchi/umod_constructiveness/pytorch_model_head.bin
-
curl -L -o pytorch_model_head.bin https://huggingface.co/emvecchi/umod_constructiveness/resolve/main/pytorch_model_head.bin
2.37 MB
- Xet hash:
- cc7c273f42557dcf1eed64f616940d9f882677f5b1d81843fd97c00ea25dbbe8
- Size of remote file:
- 2.37 MB
- SHA256:
- 49e707e6601e337d29faaa1f934d78206e0bda0fd4919a706b786f3420b8c0ab
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